Development and psychometric testing of the Canine Owner-Reported Quality of Life questionnaire, an instrument designed to measure quality of life in dogs with cancer
Bibliographic record
Abstract
OBJECTIVE To describe development and initial psychometric testing of an owner-reported questionnaire designed to standardize measurement of general quality of life (QOL) in dogs with cancer. DESIGN Key-informant interviews, questionnaire development, and field trial. SAMPLE Owners of 25 dogs with cancer for item development and pretesting and owners of 90 dogs with cancer for reliability and validity testing. PROCEDURES Standard methods for development and testing of questionnaire instruments intended to measure subjective states were used. Items were generated, selected, scaled, and pretested for content, meaning, and readability. Response items were evaluated with exploratory factor analysis and by assessing internal consistency (Cronbach α) and convergence with global QOL as determined with a visual analog scale. Preliminary tests of stability and responsiveness were performed. RESULTS The final questionnaire-which was named the Canine Owner-Reported Quality of Life (CORQ) questionnaire-contained 17 items related to observable behaviors commonly used by owners to evaluate QOL in their dogs. Several items pertaining to physical symptoms performed poorly and were omitted. The 17 items were assigned to 4 factors-vitality, companionship, pain, and mobility-on the basis of the items they contained. The CORQ questionnaire and its factors had high internal consistency (Cronbach α = 0.68 to 0.90) and moderate to strong correlations (r = 0.49 to 0.71) with global QOL as measured on a visual analog scale. Preliminary testing indicated good test-retest reliability and responsiveness to improvements in overall QOL. CONCLUSIONS AND CLINICAL RELEVANCE The CORQ questionnaire was a valid, reliable owner-reported questionnaire that measured general QOL in dogs with cancer and showed promise as a clinical trial outcome measure for quantifying changes in individual dog QOL occurring in response to cancer treatment and progression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".